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Ó¢ÎÄÕªÒª: Visual attention is an important cognitive function for the survival of humans and animals. For exploring large-scale perceptive organization in the early stage of cognitive process and a visual computational system with active environment perception, research on active visual computational model with visual attention should play an important role. This project focuses on the problem of information interaction in visual attention, exploring effective computational methods for dynamic visual information cooperation and organization, and making a breakthrough in the key techniques of object detection and tracking. The major research content involves the following components. First, based on the dynamic interaction and cooperation of different levels of retina cells, a novel motion difference detection model will be studied, which can provide a new dynamic saliency capturing approach for fast detecting of independently moving objects in video sequences. Second, in the scale of "objects", the organization of saliency in human visual attention will be explored, which aims at developing a saliency-based object detection model. Third, incorporating statistical graph theory, a robust salient object tracking model will be studied using the saliency model of objects, temporal and spatial constraints, and the dynamic difference of objects and the environment they are in. The implementation of this project will be able to provide general obstacle detection and tracking approaches for unmanned vehicle in dynamic scenes. Besides that, analyzing and categorizing video sequences can also benefit from it.
Ó¢ÎÄÖ÷Ìâ´Ê£º Visual Attention;Visual Saliceny; Object Detection; Object Tracking.
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